The GE-CMU team is developing the TIPSTER/SHOGUN system under the governmentsponsored TIPSTER program, which aims to advance coverage, accuracy, and portability in tex t interpret...
Paul S. Jacobs, George B. Krupka, Lisa F. Rau, Tod...
We describe the parser of LEU/2, the Linguistic Experimentation Environment of the LILOG project. The parser is designed to support and encourage experimentation with different gr...
Background: Advanced Text Mining (TM) such as semantic enrichment of papers, event or relation extraction, and intelligent Question Answering have increasingly attracted attention...
The complexity and diversity of government regulations make understanding and retrieval of regulations a non-trivial task. One of the issues is the existence of multiple sources o...
We extend a recently developed method [1] for learning the semantics of image databases using text and pictures. We incorporate statistical natural language processing in order to...